227-0085-38L Projects & Seminars: Controlling Biological Neuronal Networks Using Machine Learning
| Semester | Autumn Semester 2022 |
| Lecturers | J. Vörös |
| Periodicity | every semester recurring course |
| Course | Does not take place this semester. |
| Language of instruction | English |
| Comment | Only for Electrical Engineering and Information Technology BSc. Course can only be registered for once. A repeatedly registration in a later semester is not chargeable. |
Courses
| Number | Title | Hours | Lecturers | |
|---|---|---|---|---|
| 227-0085-38 P | Projekte & Seminare: Controlling Biological Neuronal Networks Using Machine Learning
 Does not take place this semester. Für den Zugang zum Angebot und zur Einschreibung loggen Sie sich hier ein (mit Ihrem n.ETHZ account): https://psapp.ee.ethz.ch/ Bitte beachten Sie, dass die Seite jeweils erst zwei Wochen vor Semesterbeginn zugänglich ist und im Verlauf des Semesters wieder abgeschaltet wird. Die Einschreibung ist nur von Freitag vor Semesterbeginn bis zum ersten Freitagmittag im Semester möglich. To access the offer and to enroll for courses log in (with your n.ethz account): https://psapp.ee.ethz.ch/ Please note that the P&S-site is accessible no earlier than two weeks before the start of the semester until four weeks after the start of the semester. Enrollment is only possible from Friday before the start of the semester until noon of the first Friday in the semester. | 2 hrs | J. Vörös |
Catalogue data
| Abstract | The category of "Laboratory Courses, Projects, Seminars" includes courses and laboratories in various formats designed to impart practical knowledge and skills. Moreover, these classes encourage independent experimentation and design, allow for explorative learning and teach the methodology of project work. |
| Learning objective | The way memory and learning is achieved in the brain is an unsolved problem. Due to its relative simplicity, in-vitro neuroscience can help us discover the fundamentals of information processing in the brain. For this we can simulate a small number of biological neurons on top of an array of microelectrodes. Such an approach allows us to simulate the electrical activity of the neurons when they get stimulated. Following this approach, we can investigate biological neural networks, that have about 5-50 neurons and a controlled network architecture. Still, their behavior remains highly unpredictable. Therefore, it is not yet clear how such networks need to be stimulated electrically in order to control their behavior. However, we can use machine learning to find a mapping between a stimulus and a desired response. More specifically, we can use reinforcement learning, since finding the right stimulation pattern is an instance of the so called multi-armed bandit problem. This P&S consists of two parts. In the first part we will introduce you to the way neurons can be simulated. You will learn how neurons work and how they communicate. The second part will be about machine learning. We will discuss the basics of both artificial neural networks (ANN) and reinforcement learning. As homework exercises you will implement a reward function for a provided reinforcement learner, which will control your biological networks. In addition you will implement an ANN, that replaces unsatisfactorily performing stimulation patterns with new patterns, that this network evaluates to perform better. If the current situation will allow, the developed ANNs will be tested on real neurons in our laboratory. This P&S will be given in English. In total, the P&S takes 8 afternoons and about 50 hours of homework (ANN implementation). |
Performance assessment
| Performance assessment information (valid until the course unit is held again) | |
Performance assessment as a semester course | |
| ECTS credits | 3 credits |
| Examiners | J. Vörös |
| Type | ungraded semester performance |
| Language of examination | English |
| Repetition | Repetition only possible after re-enrolling for the course unit. |
Learning materials
| No public learning materials available. | |
| Only public learning materials are listed. |
Groups
| No information on groups available. |
Restrictions
| General |  : Special students and auditors need a special permission from the lecturers |
| Places | Limited number of places. Special selection procedure. |
| Beginning of registration period | Registration possible from 16.09.2022 |
| Priority | Registration for the course unit is only possible for the primary target group |
| Primary target group | Electrical Engin. + Information Technology BSc (228000) |
| Waiting list | until 07.10.2022 |
| End of registration period | Registration only possible until 30.09.2022 |
Offered in
| Programme | Section | Type | |
|---|---|---|---|
| Electrical Engineering and Information Technology Bachelor | Projects & Seminars | W |  |